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Title: DNA microarray data clustering by hidden markov models and Bayesian information criterion
Authors: Phasit Charoenkwan
Aompilai Manorat
Jeerayut Chaijaruwanich
Sukon Prasitwattanaseree
Sakarindr Bhumiratana
Keywords: Computer Science
Issue Date: 1-Jan-2006
Abstract: In this study, the microarray data under diauxic shift condition of Saccharomyces Cerevisiae was considered. The objective of this study is to propose another strategy of cluster analysis for gene expression levels under time-series conditions. The continuous hidden markov model was newly proposed to select genes which significantly expressed. Then, new approach of hidden markov model clustering was proposed to include Bayesian information criterion technique which helped to determine the size of model. The result of this technique provided a good quality of clustering from gene expression patterns. © Springer-Verlag Berlin Heidelberg 2006.
ISSN: 16113349
Appears in Collections:CMUL: Journal Articles

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